Monthly Archives: November 2023

Stefan Rhys Jeske, Lukas Westhofen, Fabian Löschner, José Antonio Fernández-Fernández, Jan Bender The numerical simulation of surface tension is an active area of research in many different fields of application and has been attempted using a wide range of methods. … Continue reading →

Axel Paris, Eric Guérin, Pauline Collon, Eric Galin We present a method for interactively authoring and simulating meandering river networks. Starting from a terrain with an initial low-resolution network encoded as a directed graph, we simulate the evolution of the … Continue reading →

Y. Xu, X. Wang, J. Wang, C. Song, T. Wang, Y. Zhang, J. Chang, J. Zhang, J. Kosinka, A. Telea, X. Ban Particle-based simulations have become increasingly popular in real-time applications due to their efficiency and adaptability, especially for generating … Continue reading →

Yue Li, Stelian Coros, Bernhard Thomaszewski Nonlinear metamaterials with tailored mechanical properties have applications in engineering, medicine, robotics, and beyond. While modeling their macromechanical behavior is challenging in itself, finding structure parameters that lead to ideal approximation of high-level performance … Continue reading →

Dohae Lee, Hyun Kang, In-Kwon Lee We present ClothCombo, a pipeline to drape arbitrary combinations of clothes on 3D human models with varying body shapes and poses. While existing learning-based approaches for draping clothes have shown promising results, multi-layered clothing … Continue reading →

Yue Chang, Peter Yichen Chen, Zhecheng Wang, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun Linear reduced-order modeling (ROM) simplifies complex simulations by approximating the behavior of a system using a simplified kinematic representation. Typically, ROM is trained on input simulations … Continue reading →

Cristian Romero, Dan Casas, Maurizio Chiaramonte, Miguel A. Otaduy This paper presents a learning-based method for the simulation of rich contact deformations on reduced deformation models. Previous works learn deformation models for specific pairs of objects; we lift this limitation … Continue reading →

Zhendong Wang, Yin Yang, Huamin Wang In this paper, we address two limitations of dihedral angle based discrete bending (DAB) models, i.e. the indefiniteness of their energy Hessian and their vulnerability to geometry degeneracies. To tackle the indefiniteness issue, we … Continue reading →